code: def _get_or_create_eval_step():
      """Gets or creates the eval step `Tensor`.
  
      Returns:
        A `Tensor` representing a counter for the evaluation step.
  
      Raises:
        ValueError: If multiple `Tensors` have been added to the
          `tf.GraphKeys.EVAL_STEP` collection.
      """
      graph = ops.get_default_graph()
      eval_steps = graph.get_collection(ops.GraphKeys.EVAL_STEP)
      if len(eval_steps) == 1:
          return eval_steps[0]
      elif len(eval_steps) > 1:
          raise ValueError(
              "Multiple tensors added to tf.GraphKeys.EVAL_STEP"
          )
      else:
          counter = variable_scope.get_variable(
              "eval_step",
              shape=[],
              dtype=dtypes.int64,
              initializer=init_ops.zeros_initializer(),
              trainable=False,
              collections=[
                  ops.GraphKeys.LOCAL_VARIABLES,
                  ops.GraphKeys.EVAL_STEP,
              ],
          )
          return counter
  
imports: import math
  import time
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import init_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import state_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.training import basic_session_run_hooks
  from tensorflow.python.training import monitored_session
  from tensorflow.python.training import session_run_hook
label_desc: Use image node_id 1 for calling a global function with example usage: _get_or_create_eval_step() and returns: eval_steps, counter